Sorting data is a common problem in the big data applications space. Sorting implementations can suffer from significant limitations in practice, particularly when built from dedicated hardware (HW), but also when implemented in software (SW), where both may ultimately be subject to strict area and power constraints, relative to the scalability of critical sort capabilities. For example, a vectorized (SIMD) SW implementation of a sort algorithm is at least implicitly constrained by the vector HW core's own micro architectural limitations (only finite core HW, vector width, operational frequency & power curves, etc.), as much as a dedicated HW solution may be gate-limited in an FPGA or ASIC, forcing difficult tradeoffs that can affect not just the overall applicability of the practical implementation, but even, effectively, of the algorithm itself. Such limitations are often manifested in bounded sort key width, a characteristic fundamental to the breadth of problems the algorithm may solve.